科研之友
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摘要
Estimating the variance of the sample mean is a classical problem of steady-state simulation output analysis. Traditional batch means estimators require specification of the simulation run length a priori. To our knowledge, the Dynamic Non-overlapping Batch Means (DNBM) estimator is the only existing variance estimator that requires a constant storage space for any sample size. In this paper, we develop the Dynamic Partial-overlapping Batch Means (DPBM) algorithm, that also requires a constant storage space. In terms of the mean squared error, the statistical performance of the DPBM estimators is superior to that of the DNBM estimators.
- 出版日期2007-7
- 单位清华大学
